Measuring and testing dependence by correlation of distances

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dc.creatorSzékely, Gábor J.
dc.creatorRizzo, Maria L.
dc.creatorBakirov, Nail K.
dc.date2008-03-28
dc.date.accessioned2026-07-07T12:17:56Z
dc.date.available2026-07-07T12:17:56Z
dc.descriptionDistance correlation is a new measure of dependence between random vectors. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but unlike the classical definition of correlation, distance correlation is zero only if the random vectors are independent. The empirical distance dependence measures are based on certain Euclidean distances between sample elements rather than sample moments, yet have a compact representation analogous to the classical covariance and correlation. Asymptotic properties and applications in testing independence are discussed. Implementation of the test and Monte Carlo results are also presented.
dc.descriptionPublished in at http://dx.doi.org/10.1214/009053607000000505 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0803.4101
dc.identifierhttp://arxiv.org/abs/0803.4101
dc.identifierAnnals of Statistics 2007, Vol. 35, No. 6, 2769-2794
dc.identifierdoi:10.1214/009053607000000505
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212244
dc.subjectStatistics Theory
dc.subject62G10 (Primary) 62H20 (Secondary)
dc.titleMeasuring and testing dependence by correlation of distances
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